The Princeton Shape Benchmark provides a repository of 3D models and software tools
for evaluating shape-based retrieval and analysis algorithms. The motivation is to
promote the use of standardized data sets and evaluation methods for research in matching,
classification, clustering, and recognition of 3D models. Researchers are encouraged
to use these resources to produce comparisons of competing algorithms in future
publications.

3D Models

The benchmark contains a database of 3D polygonal models collected from the World Wide
Web. For each 3D model, there is an Object File Format (.off) file
with the polygonal geometry of the model, a model information
file (e.g., the URL from where it came), and a
JPEG image file
with a thumbnail view of the model. Version 1 of the benchmark contains 1,814 models.

Training and Test Databases

The benchmark set of models has been split into a training database and a test database.
Algorithms should be trained on the training database (without influence of the test database).
Then, after all exploration has been completed and all algorithmic parameters have been frozen,
results should be reported for the test database. In Version 1,
the training database contains 907 models, and the
test database contains 907 models.

Classifications

In order to enable evaluation of retrieval and classification algorithms, the benchmark
includes a simple mechanism to specify partitions of the 3D models into classes. In
Version 1, we provide a "base" classification that reflects primarily the
function of each object and secondarily its form. The
base training
classification contains 90 classes, and the base
test classification contains 92 classes. We also
provide coarser granularities of the base classification for
further experimentation. The base classes are merged to form
successively coarser-grained classes. In the coarsest version of
the
classification files, there are only two classes, natural and
manmade, where natural models appear in nature.

We expect that many possible classifications are possible for a given database of 3D
models. Therefore, we use a simple classification
file format to describe the classes and their members. We expect to provide
alternate classifications using this mechanism in the near future, and we encourage other
researchers to submit interesting classifications for inclusion in future versions of the
benchmark.

Software

We provide free source code to help you parse and work with the
benchmark files. For instance, we provide sample code for:
(1) parsing Object File Format
(.off) files, (2) parsing classification (.cla) files, (3) visualizing .off
files in an interactive OpenGL viewer, (4) visualizing classifications with
interactive Web pages, (5) creating plots of precision and recall for a shape
retrieval, (6) analyzing the retrieval results by a variety of
statistics, (7) viewing web pages of the retrieval results with
each model as the query, and (8) images of the distance matrix
either viewed as black and white distance values between two
models or as the first and second tier retrieval results. We hope to add more code examples in the near future.

Downloads

You can download all files in Version 1 of the Princeton Shape Benchmark, including
models, documentation, and classification files as either a zip file
(130 MB) or a gzipped tar file
(131 MB). Before downloading the files,
please send email
so that we know who is using the files and can alert you to
updates in the future.